R-Multiple and Expectancy Explained (With Worked Examples)
Ask most traders how they're doing and they'll quote a win rate or a P&L number. Both are misleading on their own. A 70% win rate can lose money. A 35% win rate can be very profitable. And P&L in dollars mixes your strategy's quality up with how much size you happened to be trading.
Two numbers cut through that: R-multiple and expectancy. If your journal tracks nothing else, it should track these.
What Is "R"?
R is the amount you planned to risk on a trade — the distance from your entry to your stop, multiplied by your position size.
If you buy at 100 with a stop at 98, and you're trading 50 shares, your risk is 2 × 50 = $100. That $100 is 1R for this trade.
Once you know R, every result can be expressed in multiples of it:
- Exit at 104 → you made $200 → +2R
- Exit at 98 (stopped out) → you lost $100 → −1R
- Exit at 101 → you made $50 → +0.5R
- Exit at 96.50 (slipped through your stop) → you lost $175 → −1.75R
The point is that R normalises every trade. A $500 win on a trade where you risked $1,000 (+0.5R) is a worse outcome than a $300 win where you risked $100 (+3R), even though the dollar number is bigger.
Why R Beats Dollar P&L
It separates skill from size. If you doubled your position size last month, your dollar P&L doubled too — for better or worse. R-multiples don't change with size, so you can compare this month to last year fairly.
It exposes bad risk management. Losses bigger than −1R mean you moved a stop, didn't use one, or got caught in a gap. If your journal shows a lot of −1.5R and −2R losses, that's a discipline problem, not a strategy problem.
It shows whether you're cutting winners. If your plan targets +2R but your average winner is +0.8R, you're exiting early. That's often a bigger opportunity than finding a new strategy.
What Is Expectancy?
Expectancy is the average R you make per trade. It's the single best number for judging whether a strategy has an edge.
The simplest way to calculate it: add up the R-multiples of all your trades and divide by the number of trades. Count breakeven trades as 0R — they're real trades, and leaving them out makes your numbers look better than they are.
You can also calculate it from its parts:
Expectancy = (Win % × Average Win in R) − (Loss % × Average Loss in R)
Worked example
Say you've taken 50 trades:
- 20 winners, averaging +2.2R
- 30 losers, averaging −1R
Win % is 40%, loss % is 60%.
Expectancy = (0.40 × 2.2) − (0.60 × 1.0) = 0.88 − 0.60 = +0.28R per trade.
That means on average, every trade you take earns 0.28 times what you risk. Risking $100 per trade, you'd expect roughly $28 per trade over a large sample — so around $1,400 over the next 50 trades, before costs.
Now look at the opposite profile:
- 35 winners, averaging +0.6R
- 15 losers, averaging −1.6R
Win rate is 70%, which feels great. But expectancy = (0.70 × 0.6) − (0.30 × 1.6) = 0.42 − 0.48 = −0.06R per trade. A high win rate, and a strategy that slowly loses money — usually because losers are held too long and winners are cut too early.
How Many Trades Before It Means Anything?
Expectancy from 10 trades is mostly noise. A handful of lucky or unlucky trades can swing it wildly. As a rough guide, treat anything under 30 trades per setup as a hint, and trust it more as the sample grows past 50–100 trades.
This is also why it's worth calculating expectancy per setup, not just for your whole account. One setup with strong positive expectancy can be hiding behind two that lose money.
Planned R vs. Actual R
The most useful comparison you can add to your journal is planned R vs. actual R: what the trade was set up to make if it hit target, versus what it actually made.
- If actual R is regularly well below planned R on winners, you're exiting early.
- If losses are regularly worse than −1R, your stops aren't being respected.
- If a specific emotion or time of day shows a big gap, that's where to focus.
How to Start Tracking This
For every trade, record at minimum: entry, stop, target, exit, and position size. From those you can calculate planned R and actual R automatically. Then review expectancy per setup at the end of each week — a weekly trading review is the natural place for it.
In Kaizen, every trade you log records its expected and actual R, the analytics page charts expected vs. actual R-multiples, and each setup in your Playbook shows its own win rate, trade count and total P&L. The quant tools include a Monte Carlo simulator, so you can see the range of outcomes your current numbers could produce — including the drawdowns you should expect even with a positive edge.
Stop asking "how much did I make?" and start asking "how much did I make per unit of risk, per trade, per setup?" That question tells you what to keep doing and what to drop.